library(lubridate)
library(ggplot2)
library(StreamMetabolism)
library(xts)
library(reshape)
library(scales)
15562 <- sunrise.set(52.45679172893955,13.774170322045896, "2024/01/01", timezone="MET", num.days=370)
sunrise <- 15562$sunrise
sunset <- 15562$sunset
sunrise <- strftime(sunrise, format="%R", tz="MET")
sunset <- strftime(sunset, format="%R", tz="MET")
15562["sr"] <- as.POSIXct(sunrise, format = "%H:%M")
15562["ss"] <- as.POSIXct(sunset, format = "%H:%M")
15562["timestamp"] <- align.time(15562$sunrise, 60*10)
15562 <- 15562[c("timestamp", "sr", "ss")]
locsrss <- ggplot(15562, aes(x=15562$timestamp)) + geom_line(aes(y=15562$sr)) + geom_line(aes(y=15562$ss)) + labs(title = " Sonnenauf-/Sonnenuntergang - 15562 2024", x = "Datum", y = "Zeit")
pdf("15562_SA_SU.pdf", paper="a4r", width=11)
locsrss
dev.off()
png(filename="15562_SA_SU.png", width = 1400, height = 800, units = "px")
locsrss
dev.off()
15562["Sonnenaufgang"] <- strftime(15562$sr, format="%H:%M")
15562["Sonnenuntergang"] <- strftime(15562$ss, format="%H:%M")
write.table(15562, file="15562_SaSu.csv", dec=',', sep=';', row.names=FALSE)